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Extract the actual text/content from a file of ANY format — PDF, Word, PowerPoint, Excel, images, scans, archives. The canonical "how do I read this file" reference, reused by process-file, Pulse ingestion, and browser downloads.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Build a designed, self-contained HTML academic map of the child's subjects, topics, and materials, plus real coaching notes for the parent on how to teach them better.
Build a designed, self-contained HTML progress report for the child — how she's actually doing, and what to work on next — surfaced in the Progress tab for both parent and child.
Create clear, child-ready study material (notes, worked examples, a revision sheet) for a topic, matched to the child's level and their own uploaded materials, packaged as one activity.
Create a practice test for the child from their materials and progress — child-facing questions with a separate parent-only answer key, packaged as one activity.
Extract genuine interest signals from the child's own conversations and keep memory/interests.md current — a Pulse-only skill, not triggered by a direct parent request.
Extract durable things the parent has said in chat and keep memory/preferences.md current — a Pulse-only skill, not triggered by a direct parent request.
| name | read-file |
| description | Extract the actual text/content from a file of ANY format — PDF, Word, PowerPoint, Excel, images, scans, archives. The canonical "how do I read this file" reference, reused by process-file, Pulse ingestion, and browser downloads. |
There is no dedicated document-reading tool — you extract the content yourself with the shell (the same approach AgentWorks uses: write a little Python and run it via execute_shell_command). Always start by identifying the file, then use the tool that is already installed for that format. Do NOT reach for a tool that isn't there (e.g. pdftotext/poppler and libreoffice/soffice are NOT installed on this machine — don't use them).
file "<path>" # what is it, really? (extension can lie)
Plain text / Markdown / CSV / JSON / code — just cat "<path>" (or head/jq for large/structured files).
PDF (digital, has a real text layer) — use pypdf (already installed), the canonical fast path:
python3 -c "import sys,pypdf; r=pypdf.PdfReader(sys.argv[1]); print('\n\n'.join((p.extract_text() or '') for p in r.pages))" "<path>"
PDF (scanned / image-only), garbled or empty pypdf output, OR any complex layout (tables, multi-column, mixed text + figures) — parse it locally with liteparse (LlamaIndex's local parser — this app's OCR/parse path). Install on demand if missing, then run in local mode so nothing leaves the machine:
pip3 install --break-system-packages liteparse # or: uv pip install liteparse
liteparse handles scanned pages, OCR, tables, and layout far better than plain extraction. For a single scanned page you may instead call the read_image tool (vision — great for handwriting/diagrams). liteparse and read_image do different jobs; use whichever fits, or both. Keep OCR/parse LOCAL — never send a file to a hosted API.
Word (.docx) — pandoc "<path>" -t plain (pandoc is installed), or:
python3 -c "import sys,docx; print('\n'.join(p.text for p in docx.Document(sys.argv[1]).paragraphs))" "<path>"
(python-docx is installed.)
PowerPoint (.pptx) — pandoc "<path>" -t plain (pandoc supports pptx input). For per-slide structure: unzip -p "<path>" 'ppt/slides/*.xml' and read the text out of the XML. For slides that are mostly images/diagrams, fall back to liteparse or read_image.
Excel (.xlsx) — use openpyxl (install on demand if missing: pip3 install --break-system-packages openpyxl), then read cells with a short Python script. Quick text dump alternative: unzip -p "<path>" 'xl/sharedStrings.xml'.
Old Office (.doc/.ppt/.xls) — no converter is installed for the legacy binary formats; liteparse is the most reliable path, otherwise ask the parent to re-save as the modern format.
Images (.png/.jpg/.jpeg/.gif/.webp/.heic — photos of notes, worksheets, handwritten homework) — you reach files as raw bytes through the shell, so you CANNOT see a picture by cat-ing it. Call the read_image tool with the path: it looks at the actual image (vision) and returns transcribed text + a description — best for handwriting, layout, and diagrams. For dense printed scans where you need raw text, liteparse also works.
Archives (.zip/.tar/.gz) — unzip -l "<path>" (or tar tf) to list, then extract and read each file inside with the rules above.
Video / audio — you cannot watch or listen. Record the filename and duration (ffprobe "<path>" if available) and ask the parent what it covers.
Anything else, or a needed tool genuinely missing — you are resourceful: pip3 install --break-system-packages <pkg> (or uv pip install <pkg>) on demand and run it locally. liteparse is the strong general-purpose fallback for most document formats.
liteparse, then read_image, then ask the parent) rather than pretending you read it.materials/, check for <file>.meta.json's extracted_text field first — process-file saves the full extraction there specifically so vision/OCR only ever runs once per file. Only fall back to actually re-reading the raw file (vision/OCR again) if that field is missing, empty, or looks truncated/wrong for what you now need (e.g. an older material processed before this field existed).